The present invention is directed to advanced analytics, data mining, and data warehousing infrastructure and services and specifically to advanced analytics, data mining, and data warehousing infrastructure and services for the healthcare industry.
The National Academy of Sciences recently reported that in the United States as many as 98,000 people die each year from medical errors. The Academy's report estimated that the total cost of preventable mistakes—not only those that lead to death, but also those that incur medical disability expenses and lost productivity—could be as high as $29 billion a year. Healthcare providers understandably would like to find solutions to these medical errors.
Analytics provides business with a tool for finding solutions to problems. Analytics can be defined variously as the science of logical analysis, the branch of logic that deals with the process of analyzing, a method of logical analysis, or the application of computer and statistical techniques to the management of information. Advanced analytics is a process of finding and interpreting patterns from data. Advanced analytics (also called data mining) is a method of helping users extract useful information from large databases. It has been used in many industries for many years to provide information that can identify opportunities, predict outcome, and reduce risk. Software such as SAS's statistic and data management products, Silicon Graphics, Inc.'s (SGI) MineSet™, Insightful Corporation's S-PLUS Analytic Server™, and business intelligence application programs, such as Cognos Incorporated's COGNOS® or Brio Technology's BRIO® provide standard platforms for the development and delivery of analytical methods. Through these analytical methods or platforms quantitative information such as financial forecasts, research and development results, business performance, transaction information, and customer behavior and prediction can be analyzed and distributed.
Healthcare involves approximately 30 billion transactions yearly. Of these, more than 3 billion are electronic. The availability of electronic healthcare data has prompted a number of warehousing initiatives (data stores). These data stores contain a wealth of detailed information useful for clinical care, research, and administration. In their raw form, however, the data are difficult to use—there is too much volume, too much detail, missing values, inaccuracies, and a diversity of database architectures. As a result, conventional healthcare data warehousing solutions relate primarily to (1) the storage and preservation of data, and (2) providing answers to known questions, either through standard reports, structured ad hoc queries (parameter driven reports), or Standard Query Language (SQL) generators that require pre-programming to modify the architecture and metadata to allow for new queries or data types.
Several companies have begun to provide healthcare analytic and warehousing services to the healthcare industry. Examples of such companies include IMS Health, Inc., Solucient (previously HCIA, Inc.), and The MEDSTAT Group, Inc. IMS Health, Inc. is a developer of healthcare information solutions and market research for the pharmaceutical sector. Solucient is a provider of financial and medical benchmark information to healthcare providers, insurance companies, and pharmaceutical companies. The MEDSTAT Group, Inc. is a healthcare information database developer and provider of healthcare “analytics.”
The analytic efforts of these companies have significant limitations. These limitations are due, in part, to their failure to successfully address a number of factors including: Health information is diverse, complex, and is not homogeneous; the architecture and composition of the analytic data stores are critical to the successful application of data mining tools; the analyst requires the ability to interactively refine the analytic model as part of the analytic process.
One example of a limitation of the known analytic efforts is that the analytic efforts of many of these companies utilize a highly structured data model and “business rules” which they incorporate in the model. The requirement for a well-defined model, governed by a set of pre-determined rules, is not suitable to data mining or knowledge discovery where the rules are yet to be discovered. For example, in order to add new elements or process new questions the model and the business rules must first be modified. Another example of a limitation of the known analytic efforts is that queries must be custom programmed or they require parameter driven or structured ad hoc queries that require a pre-defined role in the data model. Another exemplary limitation of the known analytic efforts is their need for a well-defined and limited domain such as pharmaceutical related data, UB92-hospital discharge abstracts, or insurance healthcare claims. In other words, they are not able to integrate or work across the many different data domains of healthcare. To perform advanced analysis, an analyst must be able to directly manipulate the analytic data tables, and refine these manipulations through iterative analysis. These limitations leave the known analytic efforts poorly suited for the analysis of clinical information outside of highly structured and limited domains. As a result, these analytic and warehousing services primarily answer known questions or sets of questions or simply respond to user requests for information such as reports or analysis.
Despite their claims, most of these companies focus on resource utilization and other non-clinical business aspects of healthcare. In other words, they employ financial rather than clinical data models. When they do provide clinical information it either is an expensive and time-consuming custom effort that provides a solution to answering a very specific question rather than a broad class of questions or relies on a limited list of published outcomes, such as those of the National Committee on Quality Assurance (NCQA) HEDIS® measures.
The W3Health Distributed Reporting System (DRS) network performance management module and the recently released DRS clinical performance management module are examples of analytic consulting systems. W3Health Corporation (W3Health) custom-builds this system for each healthcare organization customer. The system is primarily directed to managing risk and solving cost and utilization problems. It claims to use collected data to make better, faster decisions and gain a deeper insight into improving the quality of care. It is also available over the Internet, using an application service provider (ASP) model. The customized nature of the product makes it very expensive to implement. The system is further limited in that it requires clinical questions to be defined in advance. Further, the clinical performance management module bases much of its analysis against evidence-based medicine guidelines, DxCG, Inc.'s Diagnostic Cost Group (DCG) risk-adjustment models, HEDIS® effectiveness of care measures, and Evidenced Based Medicine (EBM) guidelines—not as a comparison to real data. Finally, W3Health's contemplated users are limited to healthcare payer and provider organizations.
The Internet is already having a significant impact on how the healthcare industry makes information available and how it processes transactions. Consumers are demanding access to Web-based healthcare information. Healthcare-related Web sites provide access to text-based information from numerous and growing electronic medical libraries. Healthcare providers are increasingly using the Internet as a means to access patient-based information, verify healthcare insurance eligibility, and process claims.
Driven in part by the Internet, the information requirements of the healthcare industry are rapidly changing. At all levels—provider, purchaser, and consumer—there is an increasing expectation that data (fact)-based information will help to improve quality, reduce cost, and support consumer choice. Most healthcare information technology environments, however, are focused primarily on supporting transactional rather than analytic systems. Recognizing the cost and complexity of creating and supporting an analytic environment, many healthcare organizations are looking for viable alternatives to buying, building, and maintaining their own analytic environment.
Companies or alliances of companies that bring their electronic commerce in healthcare transactions to the Internet include MedUnite, Inc. (MedUnite), Claimsnet.com (Claimsnet), The TriZetto® Group, Inc. (TriZetto), IMS Health, Inc. (IMS), Franklin Health, Inc. (Franklin Health), IntelliClaim, Inc. (IntelliClaim), and WebMD Corporation (WebMD). MedUnite is a consortium of major HMOs including Aetna, Inc., Oxford Health Plans, Inc., CIGNA, WellPoint Health Networks, Inc., and PacifiCare. ClaimsNet focuses on “on-line management of the $600 billion employer-based health benefit market.” IMS Health focuses on the pharmaceutical industry. Franklin Health is supported by the national alliance of Blue Cross/Blue Shield organizations. IntelliClaim is a technology-based service that provides ASP plug-in solutions for their clients' claims-performance problems. WebMD® uses the power of the Internet to serve all aspects of the healthcare industry, from consumers to medical professionals.